The Use of Artificial Neural Networks and a General Discriminant Analysis for Predicting Culling Reasons in Holstein-Friesian Cows Based on First-Lactation Performance Records

Estimation of Dairy Cow Survival in the First Three Lactations for Different Culling Reasons Using the Kaplan-Meier Method

The aims of the study were: (i) to compare survival curves for cows culled for different reasons over three successive lactations using the Kaplan-Meier estimator; (ii) to determine the effects of breeding documentation parameters on cow survival; (iii) to investigate the similarity between culling categories. The survival times for a subset of 347,939 Holstein-Friesian cows culled between 2017 and 2018 in Poland were expressed in months from calving to culling or the end of lactation. The survival tables were constructed for each culling category and lactation number. The survival curves were also compared. The main culling categories were reproductive disorders-40%, udder diseases-13 to 15%, and locomotor system diseases-above 10%. The survival curves for cows from individual culling categories had similar shapes. A low probability of survival curves for metabolic and digestive system diseases and respiratory diseases was observed in each of the three lactations. The contagious disease category was almost non-existent in the first lactation. The greatest influence on the relative culling risk was exerted by age at first calving, lactation length, calving interval, production subindex, breeding value for longevity, temperament, and average daily milk yield. A more accurate method of determining culling reasons would be required.